Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise Bayesiana de Redes Sociais× | Análise de Difusão em Redes× | |
|---|---|---|
| Área | Análise de redes | Análise de redes |
| Família | Machine learning | Machine learning |
| Ano de origem≠ | 2002 | 1927 (epidemic roots); network formalization 1990s–2000s |
| Autor original≠ | Hoff, P. D.; Raftery, A. E.; Handcock, M. S. | Kermack, W. O. & McKendrick, A. G. |
| Tipo≠ | Probabilistic / Bayesian network model | Simulation / analytical model |
| Fonte seminal≠ | Hoff, P. D., Raftery, A. E., & Handcock, M. S. (2002). Latent space approaches to social network analysis. Journal of the American Statistical Association, 97(460), 1090–1098. DOI ↗ | Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721. DOI ↗ |
| Outros nomes | Bayesian SNA, Bayesian network modeling, probabilistic social network analysis, Bayesian relational modeling | diffusion on networks, information diffusion, contagion spreading model, network propagation model |
| Relacionados | 5 | 5 |
| Resumo≠ | Bayesian Social Network Analysis applies Bayesian probabilistic inference to relational data, placing prior distributions over network parameters and updating them with observed tie data to yield full posterior distributions over structural features, tie probabilities, and latent actor positions. It enables principled uncertainty quantification in network models, making it especially valuable when data are sparse, partially observed, or subject to measurement error. | Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally. |
| ScholarGateConjunto de dados ↗ |
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